277 citations · 564 across the 48 of their papers we have counts for
5 papers · 1 filter
Approximate dynamic programming using fluid and diffusion approximations with applications to power management
Wei Chen, Dayu Huang, Ankur A. Kulkarni +5
Neuro-dynamic programming is a class of powerful techniques for approximating the solution to dynamic programming equations. In their most computationally attractive formulations,…
Interacting Multiple Model-Feedback Particle Filter for Stochastic Hybrid Systems
Tao Yang, Henk A. P. Blom, Prashant G. Mehta
In this paper, a novel feedback control-based particle filter algorithm for the continuous-time stochastic hybrid system estimation problem is presented. This particle filter is re…
Joint Probabilistic Data Association-Feedback Particle Filter for Multiple Target Tracking Applications
Tao Yang, Geng Huang, Prashant G. Mehta
This paper introduces a novel feedback-control based particle filter for the solution of the filtering problem with data association uncertainty. The particle filter is referred to…
Multivariable Feedback Particle Filter
Tao Yang, Richard S. Laugesen, Prashant G. Mehta +1
In recent work it is shown that importance sampling can be avoided in the particle filter through an innovation structure inspired by traditional nonlinear filtering combined with…
Feedback Particle Filter
Tao Yang, Prashant G. Mehta, Sean P. Meyn
A new formulation of the particle filter for nonlinear filtering is presented, based on concepts from optimal control, and from the mean-field game theory. The optimal control is c…